Discovery of Siderophore and Metallophore Production in the Aerobic Anoxygenic Phototrophs
Bibliographic record
Abstract
Aerobic anoxygenic phototrophs have been isolated from a rich variety of environments including marine ecosystems, freshwater and meromictic lakes, hypersaline springs, and biological soil crusts, all in the hopes of understanding their ecological niche. Over 100 isolates were chosen for this study, representing 44 species from 27 genera. Interactions with Fe3+ and other metal(loid) cations such as Mg2+, V3+, Mn2+, Co2+, Ni2+, Cu2+, Zn2+, Se4+ and Te2+ were tested using a chromeazurol S assay to detect siderophore or metallophore production, respectively. Representatives from 20 species in 14 genera of α-Proteobacteria, or 30% of strains, produced highly diffusible siderophores that could bind one or more metal(loid)s, with activity strength as follows: Fe > Zn > V > Te > Cu > Mn > Mg > Se > Ni > Co. In addition, γ-proteobacterial Chromocurvus halotolerans, strain EG19 excreted a brown compound into growth medium, which was purified and confirmed to act as a siderophore. It had an approximate size of ~341 Da and drew similarities to the siderophore rhodotorulic acid, a member of the hydroxamate group, previously found only among yeasts. This study is the first to discover siderophore production to be widespread among the aerobic anoxygenic phototrophs, which may be another key method of metal(loid) chelation and potential detoxification within their environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".